A social network consists of individuals and their relationships to other individuals. For example, within a company, the employees and their relationships to other employees, such as being members of the same development team or the same management committee, form a social network. Each of the employees may also have relationships to their family members and other non-family friends. Each relationship within a social network specifies a direct relationship between two individuals, such as being members of the same team. Individuals may also have indirect relationships with other individuals. For example, Tom and Mary may not know each other, but both Tom and Mary have a relationship with Jim. In such a case, Tom and Mary would have an indirect relationship to each other through Jim. The distance (number of relationships) between two individuals within a social network is commonly referred to as their “degree of separation.” For example, Tom and Mary would have two degrees of separation.
A social network that identifies individuals and their relationships with other individuals can be automatically derived from data stored by computer systems. Many individuals use their computer systems to store indications of relationships to other individuals. In particular, many software applications allow a user to explicitly store names of others with whom the user has a relationship. The names (or other identifiers such as electronic mail addresses) of the other users are stored in address lists for electronic mail programs, in contact lists for instant messaging programs, in invitation lists for event organizing programs, and so on. In addition, the names of the other users can be derived from data that is not in an explicit list. For example, the names of users can be derived from the to, from, and cc fields of electronic mail messages, from meeting entries within a calendar, from letters stored as electronic documents, and so on. Each of these other users has a relationship, referred to as a direct relationship, with the user regardless of the “closeness” of the relationship. For example, a user may have a relationship with a co-worker and a relationship with a worker at another company that was cc'd on the same electronic mail message. In this example, the relationship with the co-worker may be closer than the relationship with the worker at the other company. The users with whom a user has a relationship are referred to generally as “contacts” of that user.
Valuable information can be derived from the mining of social networks. For example, a salesperson in the sales department of company may want to make a sales pitch to a target organization, but that salesperson may not have any contacts within the target organization. Traditionally, that salesperson would either make a cold call to someone at the target organization or try to find someone who can help facilitate such a contact, such as by asking fellow employees in person or via email if they can help. The making of a cold call has disadvantages because the person called may not be the best person in the target organization to field such a call or may simply not respond to such cold calls. The asking of fellow employees also has disadvantages because the employee with the best contact may not respond or may not even be asked. The automatic mining of the social networks of the company can help identify who has a relationship with someone at that target company. Further, the automatic mining might also identify which contact at the target organization has the most relationships with employees of the company, which employee of the company has a relationship with a contact of interest at the target company (e.g., a purchasing manager), and so on.
Although valuable information can be mined from a social network, the relationships automatically derived from data stored by computer systems may be somewhat misleading. Continuing with the example, a person in the mail room of the company may store in their contact list the names and addresses of people to whom mail is sent. That person's contact list may include the president of the target organization, the purchasing manager of the target organization, and so on. The automatic mining may identify that that person has the strongest relationship with the target organization, but, of course, that person would likely not be of much help in facilitating an introduction at the target organization.